Identifying real evidence in health & nutrition studies
Main goal of the study
Best practice (especially in RCTs): pre-register outcomes and analysis plan
Example (published RCT)
“We tested the hypothesis that long-term supplementation with omega-3 fatty acids would reduce cardiovascular events in this population.”
— NEJM, 2012
Population matters for relevance
Not all studies are done on humans, and not all humans are like you.
• Cross-sectional
• Prospective cohort
• Case-control
• RCT
• Pre–post (single-arm)
• Systematic review
• Meta-analysis
Observational
• Case-control – with vs without outcome
• Case report / series – detailed look at few patients
• Ecological – group-level data only
• Retrospective cohort – past records follow exposure → outcome
Mixed / Natural
• Longitudinal – same subjects over time
• Natural experiment – exposure assigned by external factors
Interventional
• N-of-1 trial – single participant, alternating treatments
• Cross-over trial – each subject receives all treatments
• Before–after study – compare pre- vs post-intervention
Synthesis
• Systematic review – structured summary, no pooling
• Umbrella review – review of systematic reviews
Power (1 − β): the probability of finding an effect if it really exists
Usual target: 80%
Grows with bigger N, larger effect, lower noise
What type of study is this: observational, interventional, or a synthesis?
Can this design support a causal claim, or only association?
Is the control / comparison group appropriate?
For meta-analyses, are the pooled studies similar enough?
Was the sample size justified, and did they report a power calculation for the primary endpoint?
Is this effect real? How precise is it?
| Concept | What it tells us | Quick example |
|---|---|---|
| Statistical significance (p-value) | Chance vs. real effect? | Supplement ↓ BP 5 mm Hg, p = 0.03 |
| Precision (95 % CI) | How exact is the estimate? | 5 mm Hg (CI −8 to −2) |
“5 mm Hg decrease, p = 0.03” → significant
| Finding (effect) | p-value | Interpretation |
|---|---|---|
| −0.15 kg (12 wk) | 0.001 | Statistically significant; clinically trivial |
| −8.5 mm Hg systolic BP | 0.09 | Not statistically significant; could matter if real |
Know the study’s main question
It’s the foundation for understanding everything that follows.
Don’t rely on the headline / influencer.
Understand the study design
It defines what the results can tell you and how they should be interpreted.
Take into account the full body of evidence.
Don’t skip the statistics
Results are only as strong as the methods and statistical analysis behind them.
Understanding the basics goes a long way.